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daavoo
commited on
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•
85f1ae3
1
Parent(s):
fdfe90d
Add app and requirements
Browse files- app.py +176 -0
- requirements.txt +1 -0
app.py
ADDED
@@ -0,0 +1,176 @@
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1 |
+
import re
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from pathlib import Path
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import numpy as np
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import soundfile as sf
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import streamlit as st
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from document_to_podcast.preprocessing import DATA_LOADERS, DATA_CLEANERS
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from document_to_podcast.inference.model_loaders import (
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load_llama_cpp_model,
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load_tts_model,
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)
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from document_to_podcast.config import DEFAULT_PROMPT, DEFAULT_SPEAKERS, Speaker
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from document_to_podcast.inference.text_to_text import text_to_text_stream
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from document_to_podcast.inference.text_to_speech import text_to_speech
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@st.cache_resource
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def load_text_to_text_model():
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return load_llama_cpp_model(
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model_id="allenai/OLMoE-1B-7B-0924-Instruct-GGUF/olmoe-1b-7b-0924-instruct-q8_0.gguf"
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)
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@st.cache_resource
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def load_text_to_speech_model():
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return load_tts_model("OuteAI/OuteTTS-0.2-500M-GGUF/OuteTTS-0.2-500M-FP16.gguf")
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script = "script"
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audio = "audio"
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gen_button = "generate podcast button"
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if script not in st.session_state:
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st.session_state[script] = ""
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if audio not in st.session_state:
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st.session_state.audio = []
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if gen_button not in st.session_state:
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st.session_state[gen_button] = False
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def gen_button_clicked():
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st.session_state[gen_button] = True
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st.title("Document To Podcast")
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st.header("Uploading Data")
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uploaded_file = st.file_uploader(
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"Choose a file", type=["pdf", "html", "txt", "docx", "md"]
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)
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if uploaded_file is not None:
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st.divider()
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st.header("Loading and Cleaning Data")
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st.markdown(
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"[Docs for this Step](https://mozilla-ai.github.io/document-to-podcast/step-by-step-guide/#step-1-document-pre-processing)"
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)
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st.divider()
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extension = Path(uploaded_file.name).suffix
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col1, col2 = st.columns(2)
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raw_text = DATA_LOADERS[extension](uploaded_file)
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with col1:
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st.subheader("Raw Text")
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st.text_area(
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f"Number of characters before cleaning: {len(raw_text)}",
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f"{raw_text[:500]} . . .",
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)
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clean_text = DATA_CLEANERS[extension](raw_text)
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with col2:
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st.subheader("Cleaned Text")
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st.text_area(
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f"Number of characters after cleaning: {len(clean_text)}",
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f"{clean_text[:500]} . . .",
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)
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st.divider()
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st.header("Downloading and Loading models")
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st.markdown(
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"[Docs for this Step](https://mozilla-ai.github.io/document-to-podcast/step-by-step-guide/#step-2-podcast-script-generation)"
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)
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st.divider()
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st.markdown(
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"For this demo, we are using the following models: \n"
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"- [OLMoE-1B-7B-0924-Instruct](https://huggingface.co/allenai/OLMoE-1B-7B-0924-Instruct-GGUF)\n"
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"- [OuteAI/OuteTTS-0.2-500M-GGUF/OuteTTS-0.2-500M-FP16.gguf](https://huggingface.co/OuteAI/OuteTTS-0.2-500M-GGUF)"
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)
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st.markdown(
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"You can check the [Customization Guide](https://mozilla-ai.github.io/document-to-podcast/customization/)"
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" for more information on how to use different models."
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)
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text_model = load_text_to_text_model()
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speech_model = load_text_to_speech_model()
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# ~4 characters per token is considered a reasonable default.
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max_characters = text_model.n_ctx() * 4
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if len(clean_text) > max_characters:
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st.warning(
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f"Input text is too big ({len(clean_text)})."
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f" Using only a subset of it ({max_characters})."
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)
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clean_text = clean_text[:max_characters]
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st.divider()
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st.header("Podcast generation")
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st.markdown(
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"[Docs for this Step](https://mozilla-ai.github.io/document-to-podcast/step-by-step-guide/#step-3-audio-podcast-generation)"
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)
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st.divider()
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st.subheader("Speaker configuration")
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for s in DEFAULT_SPEAKERS:
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s.pop("id", None)
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speakers = st.data_editor(DEFAULT_SPEAKERS, num_rows="dynamic")
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if st.button("Generate Podcast", on_click=gen_button_clicked):
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for n, speaker in enumerate(speakers):
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speaker["id"] = n + 1
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speakers_str = "\n".join(
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str(Speaker.model_validate(speaker))
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for speaker in speakers
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if all(
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speaker.get(x, None) for x in ["name", "description", "voice_profile"]
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)
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)
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system_prompt = DEFAULT_PROMPT.replace("{SPEAKERS}", speakers_str)
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with st.spinner("Generating Podcast..."):
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text = ""
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for chunk in text_to_text_stream(
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clean_text, text_model, system_prompt=system_prompt.strip()
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):
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text += chunk
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if text.endswith("\n") and "Speaker" in text:
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st.session_state.script += text
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st.write(text)
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speaker_id = re.search(r"Speaker (\d+)", text).group(1)
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voice_profile = next(
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speaker["voice_profile"]
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for speaker in speakers
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if speaker["id"] == int(speaker_id)
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)
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with st.spinner("Generating Audio..."):
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speech = text_to_speech(
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text.split(f'"Speaker {speaker_id}":')[-1],
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model=speech_model,
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voice_profile=voice_profile,
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)
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st.audio(speech, sample_rate=speech_model.sample_rate)
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st.session_state.audio.append(speech)
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text = ""
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if st.session_state[gen_button]:
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if st.button("Save Podcast to audio file"):
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st.session_state.audio = np.concatenate(st.session_state.audio)
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sf.write(
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"podcast.wav",
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st.session_state.audio,
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samplerate=speech_model.sample_rate,
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)
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st.markdown("Podcast saved to disk!")
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if st.button("Save Podcast script to text file"):
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with open("script.txt", "w") as f:
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st.session_state.script += "}"
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f.write(st.session_state.script)
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st.markdown("Script saved to disk!")
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requirements.txt
ADDED
@@ -0,0 +1 @@
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document-to-podcast
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